What are the common normalization forms, and how do they differ?

The common normalization forms are First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), Boyce-Codd Normal Form (BCNF), Fourth Normal Form (4NF), and Fifth Normal Form (5NF).

First Normal Form (1NF) is the most basic level of normalization. It requires that the data in a relational database is free of repeating groups. In other words, each set of column must have a unique value, such that multiple columns cannot be used to fetch the same row. This helps to eliminate redundancy and improve the integrity of the data.

Second Normal Form (2NF) builds on the rules of 1NF by ensuring that all non-key attributes are fully dependent on the primary key. This means that there should be no partial dependency of any column on the primary key. For example, if a table has a composite primary key, then every other attribute in the table should be dependent on the whole key, not just part of it.

Third Normal Form (3NF) goes a step further by ensuring that all non-key attributes are not dependent on other non-key attributes. This is also known as eliminating transitive dependencies. This helps to further reduce redundancy and improve data integrity.

Boyce-Codd Normal Form (BCNF) is a stricter version of 3NF. It requires that for every non-trivial functional dependency X -> Y, X must be a superkey. This means that if a non-key attribute is functionally dependent on another non-key attribute, then the latter must be a candidate key.

Fourth Normal Form (4NF) deals with multi-valued dependencies. It requires that for any non-trivial multi-valued dependency X ->> Y, X must be a superkey. This helps to eliminate redundancy caused by multi-valued dependencies.

Fifth Normal Form (5NF), also known as Project-Join Normal Form (PJNF), deals with cases where information can be reconstructed from smaller pieces of information that can be maintained with less redundancy. It requires that every join dependency in the table is implied by the candidate keys.

Each of these normalization forms has its own specific rules and requirements, and they build on each other to progressively reduce redundancy and improve data integrity in a relational database.